Alcohol dependence (AD) is a heritable substance addiction with adverse physical and psychological consequences, representing a major health and economic burden on societies worldwide. Genes thus far implicated via linkage, candidate gene and genome-wide association studies (GWAS) account for only a small fraction of its overall risk, with effects varying across ethnic groups. Here we investigate the genetic architecture of alcoholism and report on the extent to which common, genome-wide SNPs collectively account for risk of AD in two US populations, African-Americans (AAs) and European-Americans (EAs). Analyzing GWAS data for two independent case-control sample sets, we compute polymarker scores that are significantly associated with alcoholism (P=1.64 × 10−3 and 2.08 × 10−4 for EAs and AAs, respectively), reflecting the small individual effects of thousands of variants derived from patterns of allelic architecture that are population-specific. Simulations show that disease models based on rare and uncommon causal variants (MAF<0.05) best fit the observed distribution of polymarker signals. When scoring bins were annotated for gene location and examined for constituent biological networks, gene enrichment is observed for several cellular processes and functions in both EA and AA populations, transcending their underlying allelic differences. Our results reveal key insights into the complex etiology of AD, raising the possibility of an important role for rare and uncommon variants, and identify polygenic mechanisms that encompass a spectrum of disease liability, with some, such as chloride transporters and glycine metabolism genes, displaying subtle, modifying effects that are likely to escape detection in most GWAS designs.
alcohol dependence; GWAS; polymarker scores; synthetic association; rare variants; pathway analysis
Mexican Americans are at an increased risk of both thyroid dysfunction and metabolic syndrome (MS). Thus it is conceivable that some components of the MS may be associated with the risk of thyroid dysfunction in these individuals. Our objective was to investigate and replicate the potential association of MS traits with thyroid dysfunction in Mexican Americans.
We conducted association testing for 18 MS traits in two large studies on Mexican Americans – the San Antonio Family Heart Study (SAFHS) and the National Health and Nutrition Examination Survey (NHANES) 2007–10. A total of 907 participants from 42 families in SAFHS and 1633 unrelated participants from NHANES 2007–10 were included in this study. The outcome measures were prevalence of clinical and subclinical hypothyroidism and thyroid function index (TFI) – a measure of thyroid function. For the SAFHS, we used polygenic regression analyses with multiple covariates to test associations in setting of family studies. For the NHANES 2007–10, we corrected for the survey design variables as needed for association analyses in survey data. In both datasets, we corrected for age, sex and their linear and quadratic interactions.
TFI was an accurate indicator of clinical thyroid status (area under the receiver-operating-characteristic curve to detect clinical hypothyroidism, 0.98) in both SAFHS and NHANES 2007–10. Of the 18 MS traits, waist circumference (WC) showed the most consistent association with TFI in both studies independently of age, sex and body mass index (BMI). In the SAFHS and NHANES 2007–10 datasets, each standard deviation increase in WC was associated with 0.13 (p < 0.001) and 0.11 (p < 0.001) unit increase in the TFI, respectively. In a series of polygenic and linear regression models, central obesity (defined as WC ≥ 102 cm in men and ≥88 cm in women) was associated with clinical and subclinical hypothyroidism independent of age, sex, BMI and type 2 diabetes in both datasets. Estimated prevalence of hypothyroidism was consistently high in those with central obesity, especially below 45y of age.
WC independently associates with increased risk of thyroid dysfunction. Use of WC to identify Mexican American subjects at high risk of thyroid dysfunction should be investigated in future studies.
Waist circumference; Central obesity; Thyroid dysfunction; Mexican Americans
Statistical genetic analysis of quantitative traits in large pedigrees is a formidable computational task due to the necessity of taking the non-independence among relatives into account. With the growing awareness that rare sequence variants may be important in human quantitative variation, heritability and association study designs involving large pedigrees will increase in frequency due to the greater chance of observing multiple copies of rare variants amongst related individuals. Therefore, it is important to have statistical genetic test procedures that utilize all available information for extracting evidence regarding genetic association. Optimal testing for marker/phenotype association involves the exact calculation of the likelihood ratio statistic which requires the repeated inversion of potentially large matrices. In a whole genome sequence association context, such computation may be prohibitive. Toward this end, we have developed a rapid and efficient eigensimplification of the likelihood that makes analysis of family data commensurate with the analysis of a comparable sample of unrelated individuals. Our theoretical results which are based on a spectral representation of the likelihood yield simple exact expressions for the expected likelihood ratio test statistic (ELRT) for pedigrees of arbitrary size and complexity. For heritability, the ELRT is:
where ĥ2 and λgi are respectively the heritability and eigenvalues of the pedigree-derived genetic relationship kernel (GRK). For association analysis of sequence variants, the ELRT is given by
where ht2,hq2, and hr2 are the total, quantitative trait nucleotide, and residual heritabilities, respectively. Using these results, fast and accurate analytical power analyses are possible, eliminating the need for computer simulation. Additional benefits of eigensimplification include a simple method for calculation of the exact distribution of the ELRT under the null hypothesis which turns out to differ from that expected under the usual asymptotic theory. Further, when combined with the use of empirical GRKs—estimated over a large number of genetic markers— our theory reveals potential problems associated with non positive semi-definite kernels. These procedures are being added to our general statistical genetic computer package, SOLAR.
Plasma lipidomic studies using high performance liquid chromatography and mass spectroscopy offer detailed insights into metabolic processes. Taking the example of the most abundant plasma lipid class (phosphatidylcholines) we used the rich phenotypic and lipidomic data from the ongoing San Antonio Family Heart Study of large extended Mexican American families to assess the variability of association of the plasma phosphatidylcholine species with metabolic syndrome. Using robust statistical analytical methods, our study made two important observations. First, there was a wide variability in the association of phosphatidylcholine species with risk measures of metabolic syndrome. Phosphatidylcholine 40:7 was associated with a low risk while phosphatidylcholines 32:1 and 38:3 were associated with a high risk of metabolic syndrome. Second, all the odd chain phosphatidylcholines were associated with a reduced risk of metabolic syndrome implying that phosphatidylcholines derived from dairy products might be beneficial against metabolic syndrome. Our results demonstrate the value of lipid species-specific information provided by the upcoming array of lipidomic studies and open potential avenues for prevention and control of metabolic syndrome in high prevalence settings.
high performance liquid chromatography; mass spectroscopy; phosphatidylcholine; molecular biology
Several studies have identified genes associated with alcohol use disorders, but the variation in each of these genes explains only a small portion of the genetic vulnerability. The goal of the present study was to perform a genome-wide association study (GWAS) in extended families from the Collaborative Study on the Genetics of Alcoholism (COGA) to identify novel genes affecting risk for alcohol dependence. To maximize the power of the extended family design we used a quantitative endophenotype, measured in all individuals: number of alcohol dependence symptoms endorsed (symptom count). Secondary analyses were performed to determine if the single nucleotide polymorphisms (SNPs) associated with symptom count were also associated with the dichotomous phenotype, DSM-IV alcohol dependence. This family-based GWAS identified SNPs in C15orf53 that are strongly associated with DSM-IV alcohol (p=4.5×10−8, inflation corrected p=9.4×10−7). Results with DSM-IV alcohol dependence in the regions of interest support our findings with symptom count, though the associations were less significant. Attempted replications of the most promising association results were conducted in two independent samples: non-overlapping subjects from the Study of Addiction: Genes and Environment (SAGE) and the Australian twin-family study of alcohol use disorders (OZALC). Nominal association of C15orf53 with symptom count was observed in SAGE. The variant that showed strongest association with symptom count, rs12912251 and its highly correlated variants (D′=1, r2≥ 0.95), has previously been associated with risk for bipolar disorder.
DSM-IV alcohol dependence symptoms; Family-based GWAS; C15orf53; Quantitative traits
Copy number variation (CNV) remains poorly defined in many populations, including Mexican Americans. We report the discovery and genetic confirmation of copy number variable regions (CNVRs) in subjects of the San Antonio Family Heart and the San Antonio Family Diabetes Gallbladder Studies, both comprised of multigenerational pedigrees of Mexican American descent. In a discovery group of 1677 participants genotyped using Illumina Infinium Beadchips, we identified 2937 unique CNVRs, some with observation frequencies as low as 0.002, using a process that integrates pedigree information with CNV calls made by PennCNV and/or QuantiSNP. Quantitative copy number values had statistically significant (P≤1.792e-5) heritability estimates ranging from 0.139 to 0.863 for 2776 CNVRs. Additionally, 920 CNVRs showed evidence of linkage to their genomic location, providing strong genetic confirmation. Linked CNVRs were enriched in a set of independently identified CNVRs from a second group of 380 samples, confirming that these CNVRs can be used as predefined CNVRs of high confidence. Interestingly, we identified 765 putatively novel variants that do not overlap with the Database of Genomic Variants. This study is the first to use linkage and heritability in multigenerational pedigrees as a confirmation approach for the discovery of CNVRs, and the largest study to date investigating copy number variation on a genome-wide scale in individuals of Mexican American descent. These results provide insight to the structural variation present in Mexican Americans and show the strength of multigenerational pedigrees to elucidate structural variation in the human genome.
copy number variation; Mexican Americans; MODY5; pedigree CNVRs; pedigree
Intima-media thickness (IMT) of the common and internal carotid arteries is an established surrogate for atherosclerosis and predicts risk of stroke and myocardial infarction. Often IMT is measured as the average of these two arteries, yet they are believed to result from separate biological mechanisms. The aim of this study was to conduct a family-based genome-wide association study (GWAS) for IMT to identify polymorphisms influencing IMT and to determine if distinct carotid artery segments are influenced by different genetic components.
Methods and Results
IMT for the common and internal carotid arteries was determined through B-mode ultrasound in 772 Mexican Americans from the San Antonio Family Heart Study. A GWAS utilizing 931,219 single nucleotide polymorphisms (SNPs) was undertaken with six internal and common carotid artery IMT phenotypes utilizing an additive measured genotype model. The most robust association detected was for two SNPs (rs16983261, rs6113474, p=1.60e−7) in complete linkage disequilibrium on chromosome 20p11 for the internal carotid artery near wall, next to the gene PAX1. We also replicated previously reported GWAS regions on chromosomes 19q13 and 7q22. We found no overlapping associations between internal and common carotid artery phenotypes at p<5.0e0−6. The genetic correlation between the two carotid IMT arterial segments was 0.51.
This study represents the first large scale GWAS of carotid IMT in a non-European population and identified several novel loci. We do not detect any shared GWAS signals between common and internal carotid arterial segments but the moderate genetic correlation implies both common and unique genetic components.
intima-media thickness; carotid artery; GWAS; Hispanics
The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA’s first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
Genetics; MRI; GWAS; Consortium; Meta-analysis; Multi-site
Increased serum uric acid (SUA) is a risk factor for gout and renal and cardiovascular disease (CVD). The purpose of this study was to identify genetic factors that affect the variation in SUA in 632 Mexican Americans participants of the San Antonio Family Heart Study (SAFHS). A genome-wide association (GWA) analysis was performed using the Illumina Human Hap 550K single nucleotide polymorphism (SNP) microarray. We used a linear regression-based association test under an additive model of allelic effect, while accounting for non-independence among family members via a kinship variance component. All analyses were performed in the software package SOLAR. SNPs rs6832439, rs13131257, and rs737267 in solute carrier protein 2 family, member 9 (SLC2A9) were associated with SUA at genome-wide significance (p < 1.3 × 10−7). The minor alleles of these SNPs had frequencies of 36.2, 36.2, and 38.2%, respectively, and were associated with decreasing SUA levels. All of these SNPs were located in introns 3–7 of SLC2A9, the location of the previously reported associations in European populations. When analyzed for association with cardiovascular-renal disease risk factors, conditional on SLC2A9 SNPs strongly associated with SUA, significant associations were found for SLC2A9 SNPs with BMI, body weight, and waist circumference (p < 1.4 × 10−3) and suggestive associations with albumin-creatinine ratio and total antioxidant status (TAS). The SLC2A9 gene encodes an urate transporter that has considerable influence on variation in SUA. In addition to the primary association locus, suggestive evidence (p < 1.9 × 10−6) for joint linkage/association (JLA) was found at a previously-reported urate quantitative trait locus (Logarithm of odds score = 3.6) on 3p26.3. In summary, our GWAS extends and confirms the association of SLC2A9 with SUA for the first time in a Mexican American cohort and also shows for the first time its association with cardiovascular-renal disease risk factors.
variance components decomposition approach; joint linkage/association analysis; kinship; hyperuricemia
Chromosome 7 has shown consistent evidence of linkage with a variety of phenotypes related to alcohol dependence in the Collaborative Study on the Genetics of Alcoholism (COGA) project. Using a sample of 262 densely affected families, a peak lod score for alcohol dependence of 2.9 was observed at D7S1799 (Wang et al., 2004, Hum Mol Genet). The lod score in the region increased to 4.1 when a subset of the sample was genotyped with the Illumina Linkage III panel for the Genetic Analysis Workshop 14 (GAW14; Dunn et al., 2005, BMC Genetics). To follow-up on this linkage region, we systematically screened SNPs across a 2 LOD support interval surrounding the alcohol dependence peak.
SNPs were selected from the HapMap Phase I CEPH data to tag linkage disequilibrium bins across the region. 1340 across the 18Mb region, genotyped by the Center for Inherited Disease Research (CIDR), were analyzed. Family-based association analyses were performed on a sample of 1172 individuals from 217 Caucasian families. Results: Eight SNPs showed association with alcohol dependence at p<0.01. Four of the eight most significant SNPs were located in or very near the ACN9 gene. We conducted additional genotyping across ACN9 and identified multiple variants with significant evidence of association with alcohol dependence.
These analyses suggest that ACN9 is involved in the predisposition to alcohol dependence. Data from yeast suggest that ACN9 is involved in gluconeogenesis and the assimilation of ethanol or acetate into carbohydrate.
genetics; association; linkage disequilibrium; alcohol dependence; ACN9
Nicotine dependence is a highly heritable disorder associated with severe medical morbidity and mortality. Recent meta-analyses have found novel genetic loci associated with cigarettes per day (CPD), a proxy for nicotine dependence. The aim of this paper is to evaluate the importance of phenotype definition (i.e. CPD versus Fagerström Test for Cigarette Dependence (FTCD) score as a measure of nicotine dependence) on genome-wide association studies of nicotine dependence.
Genome-wide association study
A total of 3,365 subjects who had smoked at least one cigarette were selected from the Study of Addiction: Genetics and Environment (SAGE). Of the participants, 2,267 were European Americans,999 were African Americans.
Nicotine dependence defined by FTCD score ≥4, CPD
The genetic locus most strongly associated with nicotine dependence was rs1451240 on chromosome 8 in the region of CHRNB3 (OR=0.65, p=2.4×10−8). This association was further strengthened in a meta-analysis with a previously published dataset (combined p=6.7 ×10−16, total n=4,200).When CPD was used as an alternate phenotype, the association no longer reached genome-wide significance (β=−0.08, p=0.0007).
Daily cigarette consumption and the Fagerstrom Test for Cigarette Dependence (FTCD) show different associations with polymorphisms in genetic loci.
As whole genome sequence becomes a routine component of gene discovery studies in humans, we will have an exhaustive catalog of genetic variation and the challenge becomes understanding the phenotypic consequences of these variants. Statistical genetic methods and analytical approaches that are concerned with optimizing phenotypes for gene discovery for complex traits offer two general categories of advantages. They may increase power to localize genes of interest and also aid in interpreting associations between genetic variants and disease outcomes by suggesting potential mechanisms and pathways through which genes may affect outcomes. Such phenotype optimization approaches include use of allied phenotypes such as symptoms or ages of onset to reduce genetic heterogeneity within a set of cases, study of quantitative risk factors or endophenotypes, joint analyses of related phenotypes, and derivation of new phenotypes designed to extract independent measures underlying the correlations among a set of related phenotypes through approaches such as principal components. New opportunities are also presented by technological advances that permit efficient collection of hundreds or thousands of phenotypes on an individual, including phenotypes more proximal to the level of gene action such as levels of gene expression, microRNAs, or metabolic and proteomic profiles.
The relationship between lipid metabolism with prediabetes (impaired fasting glucose and impaired glucose tolerance) and type 2 diabetes mellitus is poorly defined. We hypothesized that a lipidomic analysis of plasma lipids might improve the understanding of this relationship. We performed lipidomic analysis measuring 259 individual lipid species, including sphingolipids, phospholipids, glycerolipids and cholesterol esters, on fasting plasma from 117 type 2 diabetes, 64 prediabetes and 170 normal glucose tolerant participants in the Australian Diabetes, Obesity and Lifestyle Study (AusDiab) then validated our findings on 1076 individuals from the San Antonio Family Heart Study (SAFHS). Logistic regression analysis of identified associations with type 2 diabetes (135 lipids) and prediabetes (134 lipids), after adjusting for multiple covariates. In addition to the expected associations with diacylglycerol, triacylglycerol and cholesterol esters, type 2 diabetes and prediabetes were positively associated with ceramide, and its precursor dihydroceramide, along with phosphatidylethanolamine, phosphatidylglycerol and phosphatidylinositol. Significant negative associations were observed with the ether-linked phospholipids alkylphosphatidylcholine and alkenylphosphatidylcholine. Most of the significant associations in the AusDiab cohort (90%) were subsequently validated in the SAFHS cohort. The aberration of the plasma lipidome associated with type 2 diabetes is clearly present in prediabetes, prior to the onset of type 2 diabetes. Lipid classes and species associated with type 2 diabetes provide support for a number of existing paradigms of dyslipidemia and suggest new avenues of investigation.
Several studies have identified effects of genetic variation on DNA methylation patterns and associated heritability, with research primarily focused on Caucasian individuals. In this paper, we examine the evidence for genetic effects on DNA methylation in a Mexican American cohort, a population burdened by a high prevalence of obesity. Using an Illumina-based platform and following stringent quality control procedures, we assessed a total of 395 CpG sites in peripheral blood samples obtained from 183 Mexican American individuals for evidence of heritability, proximal genetic regulation and association with age, sex and obesity measures (i.e. waist circumference and body mass index). We identified 16 CpG sites (∼4%) that were significantly heritable after Bonferroni correction for multiple testing and 27 CpG sites (∼6.9%) that showed evidence of genetic effects. Six CpG sites (∼2%) were associated with age, primarily exhibiting positive relationships, including CpG sites in two genes that have been implicated in previous genome-wide methylation studies of age (FZD9 and MYOD1). In addition, we identified significant associations between three CpG sites (∼1%) and sex, including DNA methylation in CASP6, a gene that may respond to estradiol treatment, and in HSD17B12, which encodes a sex steroid hormone. Although we did not identify any significant associations between DNA methylation and the obesity measures, several nominally significant results were observed in genes related to adipogenesis, obesity, energy homeostasis and glucose homeostasis (ARHGAP9, CDKN2A, FRZB, HOXA5, JAK3, MEST, NPY, PEG3 and SMARCB1). In conclusion, we were able to replicate several findings from previous studies in our Mexican American cohort, supporting an important role for genetic effects on DNA methylation. In addition, we found a significant influence of age and sex on DNA methylation, and report on trend-level, novel associations between DNA methylation and measures of obesity.
The objective of this study is to identify and characterize the genetic variants related to the glomerular filtration rate (GFR) linkage on 2q37. Of the positional candidate genes, we selected IRS1 and resequenced its 2-kb promoter region and exons for sequence variants in 32 subjects. A total of 11 single nucleotide polymorphisms (SNPs) were identified. To comprehensively cover the 59-kb-long intron-1, eight additional tagging SNPs were selected from the HapMap. All the 19 SNPs were genotyped by TaqMan Assay in the entire data set (N = 670; 39 families). Association analyses between the SNPs and GFR and type 2 diabetes–related traits were performed using the measured genotype approach. Of the SNPs examined for association, only the Gly(972)Arg variant of IRS1 exhibited a significant association with GFR (P = 0.0006) and serum triglycerides levels (P = 0.003), after accounting for trait-specific covariate effects. Carriers of Arg972 had significantly decreased GFR values. Gly(972)Arg contributed to 26% of the linkage signal on 2q. Expression of IRS1 mutant Arg972 in human mesangial cells significantly reduced the insulin-stimulated phosphorylation of IRS1 and Akt kinase. Taken together, the data provide the first evidence that genetic variation in IRS1 may influence variation in GFR probably through impaired insulin receptor signaling.
Individual differences in biological ageing (i.e., the rate of physiological response to the passage of time) may be due in part to genotype-specific variation in gene action. However, the sources of heritable variation in human age-related gene expression profiles are largely unknown. We have profiled genome-wide expression in peripheral blood mononuclear cells from 1,240 individuals in large families and found 4,472 human autosomal transcripts, representing ~4,349 genes, significantly correlated with age. We identified 623 transcripts that show genotype by age interaction in addition to a main effect of age, defining a large set of novel candidates for characterization of the mechanisms of differential biological ageing. We applied a novel SNP genotype×age interaction test to one of these candidates, the ubiquilin-like gene UBQLNL, and found evidence of joint cis-association and genotype by age interaction as well as trans-genotype by age interaction for UBQLNL expression. Both UBQLNL expression levels at recruitment and cis genotype are associated with longitudinal cancer risk in our study cohort.
Transcriptional ageing; genotype by age interaction; ubiquitins; UBQLNL; cancer risk gene
Event-related oscillations (EROs) represent highly heritable neuroelectric correlates of cognitive processes that manifest deficits in alcoholics and in offspring at high risk to develop alcoholism. Theta ERO to targets in the visual oddball task has been shown to be an endophenotype for alcoholism. A family-based genome-wide association study was performed for the frontal theta ERO phenotype using 634583 autosomal single nucleotide polymorphisms (SNPs) genotyped in 1560 family members from 117 families densely affected by alcohol use disorders, recruited in the Collaborative Study on the Genetics of Alcoholism. Genome-wide significant association was found with several SNPs on chromosome 21 in KCNJ6 (a potassium inward rectifier channel; KIR3.2/GIRK2), with the most significant SNP at P = 4.7 × 10-10). The same SNPs were also associated with EROs from central and parietal electrodes, but with less significance, suggesting that the association is frontally focused. One imputed synonymous SNP in exon 4, highly correlated with our top three SNPs, was significantly associated with the frontal theta ERO phenotype. These results suggest KCNJ6 or its product GIRK2 account for some of the variations in frontal theta band oscillations. GIRK2 receptor activation contributes to slow inhibitory postsynaptic potentials that modulate neuronal excitability, and therefore influence neuronal networks.
Identification of endophenotypes (Gottesman & Gould, 2003; Gottesman & Shields, 1972) that genetically correlate with schizophrenia and are genetically homogeneous is an important strategy for detecting genes that affect schizophrenia risk. Symptoms of schizotypy may familially correlate with schizophrenia; however, there are critical limitations of the current literature concerning this association. The present study examined the genetic architecture and genetic associations between schizotypy and schizophrenia among multigenerational, multiplex schizophrenia families. Genetic schizotypy factor scales were developed that genetically correlated with schizophrenia, although some relations were unexpected in direction suggesting minimization of “psychotic-like” symptoms. These genetic schizotypy factor scales did not genetically correlate with major depressive disorder or substance dependence indicating specificity to schizophrenia. The results highlight the possibility of significant response bias in schizophrenia families, particularly among close relatives, and suggest an important consideration when acquiring self-report information. This is a topic that deserves future study as the origins of this putative bias in relatives are unclear. In addition, the results support the identification of genetic schizotypy factors as a promising technique for maximizing genetic correlation of endophenotypes with schizophrenia.
Schizotypal; Endophenotype; Relatives; Behavior genetics; Factor analysis
Recent work shows promising associations between schizophrenia and polymorphisms in Neuregulin-1 (NRG1) and a large literature also finds strong familial relationships between schizophrenia and cognitive deficits. Given the role of NRG1 in glutamate regulation and glutamate’s effect on cognition, we hypothesized that cognitive deficits may be related to variation within NRG1, providing a possible mechanism to increase risk for schizophrenia.
This study examined the associations between NRG1, cognition, and schizophrenia using a multigenerational multiplex family sample (total N = 419, 40 families), including 58 affected participants (schizophrenia or schizoaffective disorder-depressed type) and their 361 unaffected relatives. Participants were genotyped for 40 NRG1 single nucleotide polymorphisms (SNPs), chosen largely based on previous associations with schizophrenia. All participants completed structured diagnostic interviews and a computerized neurocognitive battery assessing eight cognitive domains. Variance component quantitative trait analyses tested for associations between individual NRG1 SNPs and cognitive performance in the total sample, a subsample of healthy participants with no DSM diagnosis, and using general intelligence as a covariate.
Effect sizes (within-family beta coefficients) ranged from 0.08 to 0.73, and 61 of these associations were nominally significant (p≤.05), with 12 associations at p≤.01, although none achieved the modified Bonferroni significance threshold of p<.0003. Attention was the most frequently nominally associated domain and rs10503929, a non-synonymous SNP, was the most frequently nominally associated SNP.
Although not significant experiment-wise, these findings suggest that further study of the associations between variation in NRG1 and cognition may be productive.
NRG1; attention; rs10503929
In spite of the growing recognition of the specific association of waist circumference (WC) with type 2 diabetes (T2D) and insulin resistance (IR), current guidelines still use body mass index (BMI) as a tool of choice. Our objective was to determine whether WC is a better T2D predictor than BMI in family-based settings.
Research Design and Methods
Using prospectively collected data on 808 individuals from 42 extended Mexican American families representing 7617.92 person-years follow-up, we examined the performance of WC and BMI as predictors of cumulative and incident risk of T2D. We used robust statistical methods that accounted for the kinships and included polygenic models, discrete trait modeling, Akaike information criterion, odds ratio (OR), relative risk (RR) and Kullback-Leibler R2. SOLAR software was used to conduct all the data analyses.
We found that in multivariate polygenic models, WC was an independent predictor of cumulative (OR = 2.76, p = 0.0002) and future risk of T2D (RR = 2.15, p = 3.56×10−9) and outperformed BMI when compared in a head-to-head fashion. High WC (≥94.65 cm after adjusting for age and sex) was also associated with high fasting glucose, insulin and triglyceride levels and low high-density lipoprotein levels indicating a potential association with IR. Moreover, WC was specifically and significantly associated with insulin resistant T2D (OR = 4.83, p = 1.01×10−13).
Our results demonstrate the value of using WC as a screening tool of choice for future risk of T2D in Mexican American families. Also, WC is specifically associated with insulin resistant T2D.
Infection with Epstein-Barr virus (EBV) is highly prevalent worldwide, and it has been associated with infectious mononucleosis and severe diseases including Burkitt lymphoma, Hodgkin lymphoma, nasopharyngeal lymphoma, and lymphoproliferative disorders. Although EBV has been the focus of extensive research, much still remains unknown concerning what makes some individuals more sensitive to infection and to adverse outcomes as a result of infection. Here we use an integrative genomics approach in order to localize genetic factors influencing levels of Epstein Barr virus (EBV) nuclear antigen-1 (EBNA-1) IgG antibodies, as a measure of history of infection with this pathogen, in large Mexican American families. Genome-wide evidence of both significant linkage and association was obtained on chromosome 6 in the human leukocyte antigen (HLA) region and replicated in an independent Mexican American sample of large families (minimum p-value in combined analysis of both datasets is 1.4×10−15 for SNPs rs477515 and rs2516049). Conditional association analyses indicate the presence of at least two separate loci within MHC class II, and along with lymphocyte expression data suggest genes HLA-DRB1 and HLA-DQB1 as the best candidates. The association signals are specific to EBV and are not found with IgG antibodies to 12 other pathogens examined, and therefore do not simply reveal a general HLA effect. We investigated whether SNPs significantly associated with diseases in which EBV is known or suspected to play a role (namely nasopharyngeal lymphoma, Hodgkin lymphoma, systemic lupus erythematosus, and multiple sclerosis) also show evidence of associated with EBNA-1 antibody levels, finding an overlap only for the HLA locus, but none elsewhere in the genome. The significance of this work is that a major locus related to EBV infection has been identified, which may ultimately reveal the underlying mechanisms by which the immune system regulates infection with this pathogen.
Many factors influence individual differences in susceptibility to infectious disease, including genetic factors of the host. Here we use several genome-wide investigative tools (linkage, association, joint linkage and association, and the analysis of gene expression data) to search for host genetic factors influencing Epstein-Barr virus (EBV) infection. EBV is a human herpes virus that infects up to 90% of adults worldwide, infection with which has been associated with severe complications including malignancies and autoimmune disorders. In a sample of >1,300 Mexican American family members, we found significant evidence of association of anti–EBV antibody levels with loci on chromosome 6 in the human leukocyte antigen region, which contains genes related to immune function. The top two independent loci in this region were HLA-DRB1 and HLA-DQB1, both of which are involved in the presentation of foreign antigens to T cells. This finding was specific to EBV and not to 12 other pathogens we examined. We also report an overlap of genetic factors influencing both EBV antibody level and EBV–related cancers and autoimmune disorders. This work demonstrates the presence of EBV susceptibility loci and provides impetus for further investigation to better understand the underlying mechanisms related to differences in disease progression among individuals infected with this pathogen.
Despite overwhelming evidence that major depression is highly heritable, recent studies have localized only a single depression-related locus reaching genome-wide significance and have yet to identify a causal gene. Focusing on family-based studies of quantitative intermediate phenotypes or endophenotypes, in tandem with studies of unrelated individuals using categorical diagnoses, should improve the likelihood of identifying major depression genes. However, there is currently no empirically-derived statistically rigorous method for selecting optimal endophentypes for mental illnesses. Here we describe the Endophenotype Ranking Value (ERV), a new objective index of the genetic utility of endophenotypes for any heritable illness.
Applying ERV analysis to a high-dimensional set of over 11,000 traits drawn from behavioral/neurocognitive, neuroanatomic, and transcriptomic phenotypic domains, we identified a set of objective endophenotypes for recurrent major depression in a sample of Mexican American individiauls (n=1122) from large randomly-selected extended pedigrees.
Top-ranked endophenotypes included the Beck Depression Inventory, bilateral ventral diencephalon volume and expression levels of the RNF123 transcript. To illustrate the utility of endophentypes in this context, each of these traits were utlized along with disease status in bivariate linkage analysis. A genome-wide significant quantitative trait locus was localized on chromsome 4p15 (LOD=3.5) exhibiting pleiotropic effects on both the endophenotype (lymphocyte-derived expression levels of the RNF123 gene) and disease risk.
The wider use of quantitative endophentpyes, combined with unbiased methods for selecting among these measures, should spur new insights into the biological mechanisms that influence mental illnesses like major depression.
major depression; recurrent major depression; endophenotype; endophenotype ranking; linkage; family studies
nuclear factor kappa B; gene expression network; principal components factor analysis; linkage analysis; systems genetics
We sought to identify cognitive phenotypes for family/genetic studies of successful cognitive aging (SCA; maintaining intact cognitive functioning while living to late old age).We administered a battery of neuropsychological tests to nondemented nonagenarians (n = 65; mean age = 93.4±3.0) and their offspring (n = 188; mean age = 66.4±5.0) from the Central Valley of Costa Rica. After covarying for age, gender, and years of education, as necessary, heritability was calculated for cognitive functions at three pre-defined levels of complexity: specific neuropsychological functions (e.g., delayed recall, sequencing), three higher level cognitive domains (memory, executive functions, attention), and an overall neuropsychological summary. The highest heritability was for delayed recall (h2 = 0.74, se = 0.14, p < 0.0001) but significant heritabilities involving memory were also observed for immediate recall (h2 = 0.50), memory as a cognitive domain (h2 = 0.53), and the overall neuropsychological summary (h2 = 0.42). Heritabilities for sequencing (h2 = 0.42), fluency (h2 = 0.39), abstraction (h2 = 0.36), and the executive functions cognitive domain (h2 = 0.35) were also significant. In contrast, the attention domain and memory recognition were not significantly heritable in these families. Among the heritable specific cognitive functions, a strong pleiotropic effect (i.e., evidence that these may be influenced by the same gene or set of genes) for delayed and immediate recall was identified (bivariate statistic = 0.934, p < 0.0001) and more modest but significant effects were found for four additional bivariate relationships. The results support the heritability of good cognitive function in old age and the utilization of several levels of phenotypes, and they suggest that several measures involving memory may be especially useful for family/genetic studies of SCA.
Family studies; hispanic population; neuropsychological phenotype; oldest-old; successful cognitive aging